Skip to main content

Knowledge Assessment: A Modal Logic Approach

  • Conference paper
Intelligent Agents and Multi-Agent Systems (PRIMA 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5357))

Included in the following conference series:

  • 1099 Accesses

Abstract

The possible worlds semantics is a fruitful approach used in Artificial Intelligence (AI) for both modelling as well as reasoning about knowledge in agent systems via modal logics. In this work our main idea is not to model/reason about knowledge but to provide a theoretical framework for knowledge assessment (KA) with the help of Monatague-Scott (MS) semantics of modal logic. In KA questions asked and answers collected are the central elements and knowledge notions will be defined from these (i.e., possible states of knowledge of subjects in a population with respect to a field of information).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Fagin, R., Halpern, J., Moses, Y., Vardi, M.: Reasoning About Knowledge. MIT Press, Cambridge (1995)

    MATH  Google Scholar 

  2. Huth, M., Ryan, M.: Logic in Computer Science: Modelling and Reasoning about Systems. Cambridge University Press, Cambridge (2000)

    MATH  Google Scholar 

  3. Hintikka, J.: Knowledge and Belief. Cornell University Press (1962)

    Google Scholar 

  4. Halpern, J.Y., Zuck, L.D.: A little knowledge goes a long way: Knowledge-based derivations and correctness proofs for a family of protocols. J. ACM 39(3), 449–478 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  5. Su, K., Sattar, A., Wang, K., Luo, X., Governatori, G., Padmanabhan, V.: Observation-based model for bdi-agents. In: AAAI, pp. 190–195 (2005)

    Google Scholar 

  6. Doignon, J.P.: Probabilistic assessment of knowledge. In: Dietrich, A. (ed.) Knowledge Structures. Springer, Heidelberg (1994)

    Google Scholar 

  7. Albert, D., Lukas, J. (eds.): Knowledge Spaces. Lawrence Erlbaum Associates, Mahwah (1999)

    Google Scholar 

  8. Moreno, A.: Avoiding logical omniscience and perfect reasoning: A survey. AI commun. 11(2), 101–122 (1998)

    MathSciNet  Google Scholar 

  9. Padmanabhan, V., Governatori, G., Su, K.: Knowledge assessment: A modal lgic approach. In: IJCAI Workshop on Knowledge Reasoning for Answering Questions (January 2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Padmanabhan, V., Governatori, G., Thakur, S. (2008). Knowledge Assessment: A Modal Logic Approach. In: Bui, T.D., Ho, T.V., Ha, Q.T. (eds) Intelligent Agents and Multi-Agent Systems. PRIMA 2008. Lecture Notes in Computer Science(), vol 5357. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89674-6_35

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-89674-6_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89673-9

  • Online ISBN: 978-3-540-89674-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics